windowCounts {ChIPseqR} | R Documentation |
Read counts are summarized in a sliding window of variable size with variable overlap between windows.
windowCounts(reads, window = 1000, shift = 500, method = sum)
reads |
Numeric vector of read counts. |
window |
Width of window. |
shift |
Distance between consecutive window start positions. |
method |
Function used to produce a summary for each window. It should accept a single numeric vector as argument. |
If method
returns a single value a vector of all window summaries is returned, otherwise
the return value is a list with one component for each window.
Peter Humburg
## generate some very simple artificial read data set.seed(1) fwd <- sample(c(50:70, 250:270), 30, replace=TRUE) rev <- sample(c(197:217, 347:417), 30, replace=TRUE) ## create data.frame with read positions as input to strandPileup reads <- data.frame(chromosome="chr1", position=c(fwd, rev), length=25, strand=factor(rep(c("+", "-"), times=c(30, 30)))) ## create object of class ReadCounts readPile <- strandPileup(reads, chrLen=501, extend=1, plot=FALSE, compress=FALSE) ## get number of reads in sliding window wdwCount <- windowCounts(apply(readPile[[1]], 1, sum), window=10, shift=5)